CFD Simulation Course, ANSYS Fluent for Mechanical Engineers

Explanation

The Ahmed body is a simplified vehicle model that effectively captures the fundamental flow characteristics surrounding an automobile. In addition, Ahmed's body enables us to measure aerodynamic properties that apply to automotive bodies.

This term is commonly used to describe the chaotic flow pattern around a geometry resembling a car. Once the numerical model has been validated, it can be utilized to create innovative car designs. We use a CFD solver in this study to calculate the drag values for our own experimentation.

This project investigates the behaviour of incompressible isothermal airflow in close proximity to the well-known Ahmed body geometry. The geometry involves a car with a length of 1 meter being tested inside a wind tunnel that spans 25 meters. We also chose a maximum inlet speed of 20 m/s, equivalent to a car speed of 72 Km/h.

To analyze the present issue, it is necessary to solve the flow equations in their differential form. Additionally, we consider the isothermal, incompressible, turbulent state within the wind tunnel.

For a numerical study, the first step in the modelling process involves creating the CAD geometry. We designate the blue face as the inlet of the domain and the red face as the outlet.

For the current problem, a mesh count of 624,482 elements is generated to represent the geometry accurately using ANSYS Meshing. The mesh quality is satisfactory, with a maximum skewness of 0.84 and an average of 0.22. Furthermore, for a curious reader, we have illustrated the distribution of mesh quality below. In addition, we incorporated 10 layers into our prism elements to ensure precise boundary layer calculations.

Methodology for the Study of Ahmed Body Aerodynamics

We can begin the calculation procedure once the mesh is imported into the ANSYS FLUENT solver.

In this project, gravity is a key factor we consider. The flow behaviour remains constant. This project falls under the category of pressure-based systems.

We utilized the k-w SST model to simulate the turbulence of the fluid.

In summary

Once the solution is converged, the results can be obtained through post-processing. Meanwhile, the drag and Y-plus values were closely monitored throughout the solution iterations to ensure reliable convergence.

This study determined that the solution is convergent when the drag force stabilizes consistently and the residuals fall below values of 10-5. In addition, the Y-plus value of 60 was achieved on the Ahmed body, indicating successful boundary layer resolution.

Before examining the results, it is crucial to address two significant concerns regarding the geometry of the Ahmed body. First and foremost, the Ahmed body geometry serves as a turbulent benchmark. Ahmed's body is used in cases involving the development of new turbulent models, such as the lid-driven cavity and backward step. Its accuracy is currently being tested.

The experimental results of drag, flow separation, and separation angle are compared to the data from the new model added to the CFD code for these situations. Thus, the Ahmed body allows us to validate our numerical model.

Additionally, the straightforward geometry of Ahmed's body lends itself well to LES/DES simulations, which demand precise elements. Thus, Ahmed's body of work could provide valuable insights into the intricacies of turbulence in automotive applications.

Next, the figures below show the results for the pressure and velocity fields. The corners had the highest velocity, while the middle of the front face had the highest pressure, coinciding with the minimum velocity. In addition, we present the results to provide valuable insights into the problem.

Finally, we determined that the drag force was 15.091 (N), which was precise for a car measuring 1 meter and having the specifications.

The issue involves numerically simulating the external flow of a car (AUDI) using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the model, resulting in a total of 4950697 elements.

Overview

This project uses the ANSYS Fluent software to analyze the flow of incompressible, isothermal air near an Audi-A4-2017 car. A testing speed of 77.76 m/s, which is quite high, was chosen to determine the drag force value.

Approach

The 3-D geometry of the model is created using Design Modeler software. The model features a rectangular cubic computational domain measuring 20 m * 10 m * 5 m for airflow, with an AUDI vehicle positioned within.

The model meshing has been completed using ANSYS Meshing software with an unstructured mesh type. The element number is 4950697, and the meshing accuracy is optimized near the vehicle surfaces.

In summary

Once the solution has reached convergence, the results can be observed through post-processing. Meanwhile, the drag value was closely monitored throughout the solution iterations to ensure strong convergence.

In this study, the solution reached a converged state when the drag force stabilized at a constant value, and the residuals dropped below 10-5. Based on the findings, it is evident that the primary contributors to drag forces are pressure forces, while the impact of frictional forces on drag is minimal.

The areas with the highest pressure in the car were found at the front and back. This was a result of the contour with the lowest velocity. The velocity vectors show that flow separation is present at the vehicle's front and rear.

The concentration of this separation is more pronounced in the front of the car, while it widens towards the back of the vehicle. The wider geometry at the car's rear can explain this difference. The pressure on the surface of the car body is distributed in a nearly uniform manner. However, in regions where the angle to the flow direction is greater, the pressure is elevated.

The pressure on a surface increases as it becomes more perpendicular to the flow. In addition, there is negative pressure on the sharp edges, particularly on the front wheel and the edge of the front window. The fracture's quick change in the flow angle has caused the speed in these areas to increase.

The Shear force contours also indicate the initiation of flow separation when these contours switch direction. The calculated drag force in this problem is 1684.74 Newtons.

Design Modeler and ANSYS Meshing

The problem involves numerically simulating airflow in a Jet Intake using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the mesh for the model, resulting in a total of 389,136 elements.

Overview

The current problem involves simulating the airflow in a three-dimensional Jet Intake using ANSYS Fluent software. We conducted this CFD project and analyzed it using CFD analysis.

The current model has been created in three dimensions using Design Modeler software. The model's geometry features a cylindrical computational domain with the jet intake positioned.

The meshing of this current model has been generated using Ansys Meshing software. The total number of cells is 389136.

Approach to Intake

For this project, the steady airflow in a three-dimensional jet intake is being investigated using ANSYS Fluent software. Jet engines are a crucial component of aircraft propulsion systems and are widely utilized in the field of aviation. In this case, jet engines, such as the intake section, are utilized for both subsonic and supersonic flows.

In subsonic flows, the velocity of the flow is greater than the free stream velocity within the intake domain. On the other hand, in supersonic flows, the Mach number of the flow increases within the intake domain. The intake is the initial section where incoming air is directed towards the engine.

The intake geometry is adjusted to ensure consistent airflow by altering the cross-section. In this project, air flows into the domain at a velocity of 3.55 m/s. In addition, the k-epsilon model is employed to solve equations governing turbulent fluid flow.

Final Thoughts

After completing the solution process, you will obtain contours that depict pressure, velocity, streamlines, and velocity vectors in both two- and three-dimensional formats. In addition, according to the data calculated using the Fluent software, the air mass flow rate in the intake domain is 0.02525548 kg/s.

As a result of an unexpected reduction in the cross-section of fluid flow, the velocity inside the intake reaches significantly higher magnitudes, measuring 3.6 m/s. Before entering the intake area, the airflow pressure increases to 5.96 Pa due to the abrupt reduction in flow cross-section.

The problem involves numerically simulating methane gas flow through an orifice using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create a mesh for the model.

The mesh type is structured, and the element number is 54648.

Overview

The problem involves simulating methane gas flow through an orifice within the canal using ANSYS Fluent software. We conducted this CFD project and analyzed it using CFD analysis.

A basic orifice model consists of a perforated plate positioned perpendicular to the fluid flow path in the desired channel. The current model has been created using Design Modeler software in three dimensions.

The model features a channel that measures 12 inches in length and 0.5 inches in diameter. In the center of the channel, there is a cross-sectional reduction means with a diameter of 0.25 inches.

The meshing of the current model has been completed using ANSYS Meshing software. The mesh type is Structured, and the element number is 54648.

Methodology for Orifices

The orifice is commonly used for measuring mass flow with pressure difference transmitters.

The operating mechanism of the orifices causes an increase in fluid velocity as it passes through. This is due to the reduction in the cross-sectional area of the flow, in accordance with the law of mass conservation, flow constant, and the Bernoulli principle.

Similarly, as the fluid exits the orifice, the flow velocity decreases once more because of the expansion in the cross-sectional area of the flow. Consequently, the pressure of the flow rises.

Consequently, a pressure difference arises on either side of the orifice, which is then measured using pressure transmitters and integrated pressure sensors.

Consequently, the orifice flow meter utilizes an equal pressure difference to determine the flow rate of the fluid moving through the designated channel, considering the pressure drop and the ratio of the orifice hole diameter to the channel diameter.

The fluid being analyzed in this simulation is methane gas. It has a density of 0.6679 kg/m3 and a viscosity of 0.00001087 kg/m.s. The flow enters the channel with a velocity of 0.033 m/s and exits at atmospheric pressure.

In addition, the RNG k-epsilon model is employed for solving turbulent fluid equations.

Final Thoughts on the Orifice

After completing the solution process, you will obtain contours depicting velocity and pressure in two-dimensional and three-dimensional forms. Additionally, a diagram illustrating the variations in pressure and velocity along the central axis of the channel and across the section of the orifice has been acquired.

The diagrams and contours show that the flow velocity experiences abrupt changes as the fluid passes through the orifice, caused by a sudden alteration in the cross-sectional area. One can also observe the pressure drop in the fluid flow as it passes through the orifice section.

Description of the Lubrication Project

This problem involves simulating the impact of lubrication on the friction factor between the cylinder and the ring in an engine. It takes into account different groove texture patterns using ANSYS Fluent. The motion of the ring on the inner surface of the cylinder in an engine results in the generation of friction between the surfaces. One way to decrease friction between surfaces is through the lubrication process. This involves pouring oil into the gap between the two surfaces. This model features oil with a 900 kg.m-3 density, specific heat capacity of 210 j.kg-1.K-1, thermal conductivity of 0.13 Wm-1.K-1, and viscosity of 0.04 kg .m-1.s-1.

There are grooves on the inner surface of the cylinder where the oil flows in the space between them. These surfaces can be designed with various patterns depending on the angle and density of the grooves applied to them. In the current modeling, four different patterns have been utilized for these grooves, encompassing angles of 30, 45, 60, and 90 degrees. The current project seeks to explore the friction coefficient level generated on the moving ring's surface. The current simulation defines a square computational area where multiple rows of grooves with specific angles are designed.

Description of the Lubrication Project

The lower surfaces of this area and its grooves are classified as a static wall, while the smooth upper surface of the area is considered a moving wall. Given the nature of this square area as a sample space of a general computational area, it is worth noting that the lateral surfaces of the grooves exhibit a symmetric boundary condition. The lower stationary wall maintains a constant temperature of 353 K, while the upper moving wall remains at a steady temperature of 393 K. Due to the variation in groove angles, the oil flow path within the grooves will differ due to the four distinct modeling patterns.

Now, let's consider that when a surface moves rapidly on these grooves, its path creates an angle that is half the angle between the two grooves. So, we use the bisector of these angles to determine the velocity of the moving wall in relation to its side grooves. This wall can move at a velocity of 10 m/s in all four modes. By utilizing the sine and cosine functions for angles of 15, 22.5, 30, and 45 degrees, it is possible to achieve varying velocities in two distinct coordinate directions.

Geometry and mesh

The current model is created in three dimensions using Design Modeler software. The model features a square computational area with a dimension of 0.001 m for fluid flow. This computational area features 20 rows of grooves, each with a depth of 0.000006 m. The rows of grooves are intentionally oriented in two different directions, creating varying angles between them. The grooves are carefully designed with four different patterns, each with specific angles in relation to one another. These patterns include angles of 15, 30, 45, and 90 degrees.

The present model has been meshed using ANSYS Meshing software. The mesh type has a structured design, and the element numbers for grooved modes at angles of 30, 45, 60, and 90 degrees are 633774, 645574, 642332, and 692403, respectively. Here is a visual representation of the mesh for the 60 ° groove mode.

Simulation of Lubrication using CFD

To simulate the current model, we take into account several assumptions:

We utilize a pressure-based solver in our operations.

The simulation is stable.

The fluid's response to gravity is disregarded.

Outcome

After completing the solution process, you will obtain three-dimensional contours for pressure, velocity, and temperature and a two-dimensional friction coefficient contour and plots.

The issue involves the numerical simulation of heat transfer in brake disks using ANSYS Fluent software.

We utilized the Gambit software to create the 3-D model.

We use Gambit software to mesh the model, resulting in 32884 elements.

We have two disks, one being the Stationary wall and the other being the Moving wall.

Explanation

For this project, we simulated the heat transfer process in brake disks and thoroughly analyzed the results using ANSYS Fluent software.

The current model is created in 3-D using the Gambit software. The geometry is connected to a brake disk that experiences a rise in temperature due to the friction force generated during braking.

The meshing of this current model has been generated using Gambit software. The total cell count exceeds 32884.

Approach to Brake Disk

Disks are a commonly utilized component in various industries. Design engineers in mechanics have always considered the study of the disks' performance and how their rotation affects each other.

The heat of the rotation and friction between the disks can negatively impact their durability and overall performance.

Brake disk simulation, heat generation analysis, heat transfer between the disks, and their surroundings are key topics extensively discussed in the industry.

For this project, the heat transfer process in brake disks is simulated using ANSYS Fluent software. The object labeled "Disk2" exhibits a rotational motion, spinning at a speed of around 343rpm. The rotating motion of Disk 2 has been implemented by utilizing the moving wall option.

The current disks all have a temperature of 343 K. Given the stationary nature of "Disk1," it will inevitably decrease the speed of "Disk2" and the generation of friction.

The laminar model is utilized to solve fluid flow equations, while the energy model is activated to calculate the temperature distribution within the computational domain.

Conclusion on the Brake Disk

Various contours are obtained after the simulation, including those for pressure, temperature, skin friction coefficient, and more.

As observed in the temperature contour, the friction exerted on the fluid and disk increases their temperatures. In addition, the streamline and velocity vector results clearly show the rotational motion of Disk 2.

The problem involves numerically simulating the Container Effect on Truck aerodynamics using ANSYS Fluent software.

The 3-D geometry is created using Solidworks and Design Modeler software.

We utilized ANSYS Meshing to create a polyhedral mesh. The number of elements is 663,127 for 'truck' and 1,095,371 for 'truck and container.'

Turbulence is represented using the k-w SST model.

Explanation

Understanding aerodynamics is crucial when it comes to designing cars. It is crucial to consider this aspect when designing a truck. Given their heavier weight, minimizing air resistance is essential for optimizing their forward movement. Air resistance to forward motion, also known as drag force, is a crucial factor.

By conducting an aerodynamic CFD simulation of the truck and calculating the drag force, we can accurately predict the forces at play, particularly those surrounding the truck. This directly impacts the truck's fuel consumption and is crucial from an energy and environmental standpoint.

This project uses ANSYS Fluent software to analyse the truck's drag force and compares it in two scenarios, with and without a container.

First, the truck's geometry is carefully crafted using Solidworks and Design Modeler software. The geometry is prepared for meshing and name selection and then implemented in ANSYS Meshing software. In addition, the mesh type is polyhedral, resulting in 663,127 elements for 'truck' and 1,095,371 elements for 'truck and container.'

Okay.

Methodology for CFD Simulation of Truck Aerodynamics and the Impact of Containers

To conduct flow simulation and investigation, a comparison was made between two truck modes, one with containers and one without. We opted for the k-w SST turbulence model with standard wall function to improve the accuracy of our simulation. The pressure-and-momentum coupling method is straightforward.

The solver employed is pressure-based.

In summary

We must discuss geometry, meshing, boundary conditions, fluid properties, the Y-plus (Y+) criterion, and the results. We will analyze both modes' speed, pressure, and drag force and determine the most effective mode for reducing drag.

Based on the findings, it is evident that the drag force is lower when the container is not present than when it is. It is more efficient to transport the truck without the container. Indeed, when the issue is confined to the two sections at the rear of the truck and the back of the container, the presence of the container can cause a delay in the separation of flow in the back of the truck.

However, the delay in separation results in a reduced drag caused by the flow from the end of the container, which has a smaller angle than the edge of the roof of the new truck. The images depicting the flow lines behind the truck and container reveal the significant intensity of the vortices, particularly from the angle of the top edge of the truck in empty truck condition. This result is evident in the pressure coefficient diagram for comparing the two.

The problem involves the numerical simulation of an injector using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the model's mesh, resulting in a total of 102,752 elements.

We utilize the VOF Multi-Phase model to accurately characterize the presence of water and air within the injector.

The ANSYS Fluent software simulates multi-phase flow in an injector for this project. We conducted this CFD project and analyzed it using CFD analysis.

The current model is created in three dimensions using the Design Modeler. There are three ducts with different shapes for water flow: a square cross-section, a conical-shaped area, and a cylindrical chamber. The current project's meshing was accomplished using ANSYS Meshing software. The element number is 102752.

Approach

The VOF Multi-Phase model is utilized, incorporating air and water flows. The water flow is directed through three curved ducts, ultimately leading to a reservoir filled with airflow.

The curved design of the ducts and the conical shape of the air-filled tank help to evenly distribute the water flow vortices into the injector, effectively expelling the water from the vicinity of the cylindrical chamber near the chamber wall.

The water flow is introduced through the inlet boundary at a mass flow rate of 0.01 kg/s. In addition, the k-epsilon model is capable of solving turbulent fluid equations.

In conclusion

After completing the solution process, various contours are obtained inside the injector, providing information about temperature, velocity, air and water volume fraction, streamlines, and more.

As observed in the water volume fraction contour, the water is injected through the curved channels and then flows through the cylindrical space. The curved channels create a swirling effect in the water flow, ensuring the rotation occurs within the cylindrical space.

The issue involves the numerical simulation of phase change materials (PCM) in a storage tank using ANSYS Fluent software.

We create the 2-D model using the Design Modeler software.

We utilize ANSYS Meshing software to mesh the model. Additionally, a density-based solver is employed to define the compressible flow accurately.

The mesh type is structured, and the number of elements is 9000.

The current study models the separation of flow within a supersonic convergent-divergent nozzle. It analyzes the airflow separation from the nozzle in the surrounding environment using ANSYS Fluent software. We conducted this CFD project and examined it through CFD analysis.

The design of the nozzle allows for an increase in fluid velocity as it passes through the convergent part. The continuity equation requires reducing the flow's cross-sectional area to achieve this. Thus, as per Bernoulli's law, the fluid pressure decreases as the velocity increases.

The motion of the fluid flow in the longitudinal direction of the nozzle determines parameters like Mach number, velocity, and pressure, which have been the subject of investigations to analyze this model.

Here is a diagram illustrating the internal structure of a convergent-divergent nozzle and its various components.

The current 2-D model has been created using Design Modeler software. The model's geometric structure includes a convergent-divergent nozzle, a throat area, and a rectangular space that houses the nozzle output.

The meshing of the current model has been completed using ANSYS Meshing software. The mesh type is well-organized, and the element count is 9000.

Approach

We have implemented a density-based solver to account for the compressibility of this project. The nozzle pressure ratio (NPR) represents the relationship between the inlet air pressure of the nozzle and the ambient pressure.

In the current system, the nozzle pressure ratio is 1.5, and the inlet air pressure is 153580.65 Pascals. The pressure at the output is equal to the ambient pressure, which is 102387.146 Pascal.

Furthermore, the incoming airflow is at a temperature of 290 Kelvin.

In summary

After completing the solution process, we can generate two-dimensional contours of various parameters such as pressure, temperature, velocity, density, Mach number, and two-dimensional path lines.

From the shape of the contours, it is evident that there has been an increase in Mach at the nozzle opening. Thus, this particular nozzle alters the Mach number as it enters the range by modifying the cross-section.

By increasing the Mach number in the nozzle opening, the pressure and temperature in the nozzle decrease accordingly.

The problem involves the numerical simulation of the discrete phase trap (TRAPPER) using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the model, resulting in 420,485 elements.

We utilize the Discrete Phase Model (DPM) to establish the particle trapping mechanism.

In this project, we have endeavored to simulate and analyze the flow of a particle trapping mechanism using the ANSYS Fluent software. We conducted this CFD project and analyzed it using CFD analysis.

We work with discrete phase flows in various mechanical and engineering systems, and their application is rising. Thus, to enhance the efficiency of systems, it is crucial to possess a comprehensive understanding of these flows.

Multi-phase flows can be classified into various groups, and one of these groups includes dispersed multiphase flows, which are frequently encountered in engineering systems. Dispersed multi-phase flows encompass various types of flows, such as bubble flow, droplet flow, and particle flow.

Within this process, a particular phase is designated as the carrier phase, where particles, bubbles, and droplets disperse and give rise to additional phases. CFD simulation is crucial for optimizing the design of distributed multi-phase flow systems.

With a speed of 5 m/s, the flow enters the computational domain, consisting of continuous and dispersed phases.

The geometry of this model is created using the ANSYS design modeler and then meshed using ANSYS meshing software. The geometry utilizes an unstructured mesh type with an element number of 420485.

Methodology for Trapping Utilizing a particle trapping mechanism known as the discrete phase trap (TRAPPER) through ANSYS Fluent software.

To simulate the particles, we activate the discrete phase model and apply the Saffman lift force and pressure gradient forces to them.

In addition, the trapping mechanism has been designed to consider the effects of gravity.

Final Outcome

The presentation showcases the contours, pressure, velocity, and particle tracks, among other details. The results indicate that approximately 45.26% of the particles have been captured. Particles significantly impact fluid flow, causing velocities to rise in regions with higher particle densities.

The issue involves the numerical simulation of the fuel injector using ANSYS Fluent software.

We created the 3-D model using the Gambit software.

We use Gambit software to mesh the model.

The mesh type is structured, and the element number is 932107.

We utilize the Mixture Multi-Phase model to establish the presence of three distinct phases: air, liquid, and vapor.

This simulation focuses on a fuel injector using ANSYS Fluent software. We conducted this CFD project and analyzed it using CFD analysis.

Typically, a fuel injector is a complex arrangement of ducts and nozzles that efficiently controls the flow of fluids at varying pressures. This pump operates using fluid dynamics and only requires a valve to regulate the incoming flow, making it highly efficient.

This principle is applied through a steam injector, which delivers cold water to a boiler by utilizing its own live or exhaust steam, eliminating the need for a mechanical pump.

In this project, we have simulated a three-phase flow fuel injector. This mixture contains liquid, air, and vapor. A jet flow is formed inside as the liquid enters the computational zone through the injector at a velocity of 20 m/s.

The geometry of the current model is created using Gambit software. This model features a combustion chamber with a fuel injector and an air inlet.

The model is meshed using Gambit software. A structured model mesh has been created, consisting of 932107 cells.

Method for Fuel Injection

In this simulation, three different fluids are utilized within the computational zone. These three phases consist of air, liquid, and steam.

Next, the multiphase model is utilized. The mixture model is employed given the ambiguous separation boundary between the phases. In this model, the phases are thoroughly blended together. The primary phase is air, while the secondary phases are vapor and liquid.

The outcome of the Fuel Injector

The pressure, velocity, and mass fraction contours for liquid, air, and vapor are obtained after the simulation. The contours suggest that the liquid flow enters the combustion chamber with significant velocity and pressure, filling the entire space.

The contour comparison of each mixture phase indicates that the multiphase flow modeling has been executed accurately.

Design Modeler and ANSYS Meshing

The issue involves the numerical simulation of the Axial Pump using ANSYS Fluent software.

We utilized the SpaceClaim software to create the 3-D model.

We use ANSYS Meshing software to mesh the model, resulting in a total of 36,865 elements.

The Single Reference Frame is used to simulate rotational motion.

Explanation

For this project, a numerical simulation method called CFD was used to simulate the performance of an axial pump. The fluid flow in axial pumps is aligned with the impeller shaft axis. Certainly, there are various kinds of axial pumps. The flow direction within them can vary between the radial and axial directions.

When high fluid flow and low head are needed, axial pumps are ideal. For this project, the water enters at a velocity of 2 m/s and exits at atmospheric pressure. The pump impeller is rotating at a speed of 200 rpm, and the Frame Motion module has been utilized.

The two-dimensional geometry was created using SpaceClaim software. The dimensions of the commutating domain are 118 mm in length and 117 mm in width. Furthermore, the meshing was completed using ANSYS Meshing software, and the elements used were unstructured. In addition, there are a total of 36,865 elements.

This CFD project is part of the ANSYS Fluent General Training Course, specifically the 9th episode.

Approach: Single Reference Frame (SRF) Axial Pump

A pressure-based solver is used because water is incompressible. The gravitational acceleration is not taken into account. In addition, the simulation is conducted in a steady state. The Axisymmetric Swirl option is utilized in this case. The rotational motion of the flow is simulated using MRF.

In summary

Upon analyzing the simulation, it becomes evident that the velocity's radial component at the output increases in relation to the input, owing to the blade's rotational speed. In addition, the dynamic pressure increases in direct correlation with the fluid's velocity.

The problem involves the numerical simulation of Turbine Blade Cooling using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the model, resulting in a total of 10,154,723 elements.

We utilize the Energy Equation and implement thermal boundary conditions on the turbine blades.

Overview

The current issue involves simulating the cooling of a turbine blade using ANSYS Fluent Turbine. We conducted this CFD project and analyzed it using CFD analysis.

To simplify the problem model, we will only simulate one blade, considering the symmetrical structure of the turbine body and its blades. The primary objective of the problem is to analyze the temperature distribution and variations in thermal energy across the body and turbine blade.

Thus, the simulation process involves modeling and setting boundary conditions to analyze heat transfer in the fluid specifically.

The cooling process in this model relies on the concept of airflow within the inner walls of the blade to maintain a cool temperature. These inner walls feature a series of strategically placed holes to optimize contact with the cold flow, enhancing the cooling process.

The current 3-D model is created using CATIA software and then imported into the Design Modeler software. The meshing of the current model has been completed using ANSYS Meshing software. The mesh type is unstructured, and the element count is 10154723.

Approach to Turbine Blade Design

The heat transfer boundary condition has been applied to the surfaces of the blade's outer and inner walls. The blade's outer surface and lower body, exposed to the hot working airflow, have a transfer coefficient of 200 watts per cubic meter and a temperature of 1672 Kelvin.

On the other hand, the cold airflow cools the blade's inner surface, resulting in a heat transfer coefficient of 200 watts per cubic meter when exposed to a cold flow of 300 Kelvin.

Final Thoughts on Turbine Blades

Once the solution is finished, temperature contours in both 2-D and 3-D are obtained within the space between the outer and inner walls of the blade. The outer wall is in contact with the hot flow, while the inner wall is in contact with the cooling flow.

In addition, the heat transfer coefficient is determined for both the inner and outer walls of the blade and the blade base.

The contours in the XZ section are depicted at various distances from the upper surface of the blade base, including 0.004, 0.016, 0.028, and 0.04 meters. Similarly, the XY section also displays contours at different distances.

The problem involves the numerical simulation of a centrifugal blower using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the model mesh, resulting in 172,824 elements.

We utilize the frame motion method to establish rotational motion within cell zone conditions.

Overview

This simulation focuses on a centrifugal blower using ANSYS Fluent software. We conducted this CFD project and examined it through CFD analysis.

The blower is a device that blows high-pressure air for various purposes, such as dust cleaning. As an illustration, a blower is employed to clean computer parts and equipment effectively.

Similar to the work of a mechanical engineer, the central motor of this device generates rotational motion, creating high pressure in the air. This high-pressure air is then directed out of the device's outlet. The blower designed in this model is of the centrifugal type.

The centrifugal blower efficiently draws in air through its central section, allowing the airflow to enter the central impellers smoothly in a fin disc configuration. The high-speed rotation of the blades also induces the airflow to rotate.

The centrifugal force enhances the air pressure, resulting in a higher airflow velocity. Ultimately, the high-pressure air is channeled to the external environment via a duct strategically positioned on the blower's outer casing.

The current model has been created in two dimensions using Design Modeler software. This model is a two-dimensional centrifugal blower that has been specifically designed to minimize computational expenses. Given the nature of the blower, the input is received at the center of the model, while the output is situated at the perimeter.

The model is meshed using ANSYS Meshing software. An unstructured model mesh has been generated, consisting of 172824 cells.

Centrifugal Blower Technique

In this simulation, a specific area surrounding the blades is separated from the rest of the computational domain to represent the rotational airflow accurately. The frame motion has been implemented in the cell zone conditions for this specific zone.

Assuming that instead of defining rotational motion for the blades at a given speed, rotational flow is defined for the air around the blades at the same speed. This rotational motion has a speed of 260 rad/s.

In addition, the model's significance is tied to variations in pressure, so the pressure boundary condition is applied at both the input (central part of the model) and the output (outer part of the model).

Final Thoughts on the Centrifugal Blower

Following the simulation, we have obtained two-dimensional contours of pressure, velocity, and turbulence kinetic energy. In addition, the analysis yields two-dimensional pathlines and two-dimensional velocity vectors.

Based on the findings, it is evident that the airflow is directed toward the central section of the blower and undergoes a rotational motion with high pressure in the regions surrounding the blades. Next, the airflow experiences a boost in pressure and speed, causing it to be expelled from the blower outlet.

The problem involves the numerical simulation of a centrifugal compressor with a diffuser using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the model, resulting in 303600 elements.

We utilize the frame motion method to establish rotational motion for the centrifugal compressor.

This simulation focuses on a centrifugal compressor (ANSYS Fluent CFD Simulation) with a diffuser. We conducted this CFD project and analyzed it using CFD analysis.

The centrifugal-type compressor is highly popular and widely utilized in various industries. This compressor utilizes positive pressure and centrifugal force to compress the gas efficiently. As the compressor impellers rotate, they draw in low-pressure air from the central axis and increase its pressure.

The compressed air is then expelled radially from the diffuser section surrounding the compressor. We have chosen to model only one of the blades for efficiency and cost reduction. This decision is based on the compressor's symmetrical structure and the blades' similarity.

The geometric model of each blade consists of an in-block connected to the input and a passage connected to the output. The hub and shroud covers are positioned on opposite sides of each blade, creating a space where the blades are situated.

The compressor blade spins on its central axis (z-axis) at a rapid rotational speed of 800 rpm. The reason for the diffuser in the air path after each blade is the rise in air pressure. After leaving the central part of the compressor, the fluid possesses kinetic energy and potential.

By adjusting the output velocity of the compressor blades, one can effectively increase the amount of outlet fluid pressure. This is due to the inverse relationship between the pressure changes in the passing fluid and the square of the fluid velocity, as stated in the Bernoulli relation.

This rise in pressure contributes to enhancing the operational efficiency of the compressor. Thus, a diffuser is employed in the compressor. As the cross-section of the fluid passage expands, the velocity of the passage decreases. Consequently, the outlet fluid pressure rises as the fluid velocity decreases.

The current model has been created using Design Modeler software in two dimensions. The model is meshed using ANSYS Meshing software. An unstructured model mesh has been generated, consisting of 303600 cells.

Computational Fluid Dynamics (CFD) Method

For this simulation, it is necessary to specify the rotational movement of the fluid surrounding the compressor blade. Rotational motion is defined using the Frame Motion method in cell zone conditions.

It is assumed that the blade, acting as a boundary, has no rotational movement, while the passage circumference and the attached wall (hub) have a rotational velocity of 800 rpm in the section frame motion.

In summary

Upon simulation, the compressor blade surface reveals two-dimensional contours of pressure and stress. Obtained: three-dimensional contours of pressure, temperature, velocity, and turbulent kinetic energy on the compressor blade. Obtained: 3D velocity vectors have also been acquired.

The fluid's pathlines clearly illustrate the compressor's centrifugal nature, as the fluid flows radially outward from the central part. In addition, the variations in pressure and speed surrounding the blade are clearly depicted, resulting from the rotational motion of the compressor.

The problem involves the numerical simulation of a multistage compressor with 2 rotors and 2 stator rows using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ANSYS Meshing software to create the model, resulting in 972,354 elements.

We utilize the Fram Motion method to establish rotational motion for our compressor.

This simulation involves a multistage compressor with 2 rotors and 2 stator rows using ANSYS Fluent software. We conducted this CFD project and examined it through CFD analysis.

The simulation involves the design of an axial compressor with four rows comprising stator and rotor components. Typically, axial flow compressors are compressors that have airflow running parallel to the axis of rotation.

There are two main components in axial compressors: the rotor and the stator. The rotors are rows connected to the central shaft and rotate incredibly fast around the compressor's central axis. Stators, however, remain stationary and lack rotating components.

The main purpose of rotors is to generate torque and increase airflow speed by rotating. The main purpose of stators is to enhance air pressure and prevent its swirling motion around the compressor's axis by balancing the airflow parallel to the axis.

Put simply, the stators transform the heightened kinetic energy within the compressor into static pressure and alter the airflow's direction, preparing it to enter the subsequent rotor. This simulation involves the differentiation of two sections known as stators and two sections known as rotors.

The current model has been created in two dimensions using Design Modeler software. The model consists of two rows of the rotor and two rows of the stator. Every row of the stator or rotor comprises 22 blades featuring an airfoil cross-section.

The rotor blades exhibit deflection, while the stator blades remain in a fixed horizontal position. For efficiency, we have designed only one blade for each row of stator and rotor in this geometry. Additionally, we have utilized the periodic boundary condition for the lateral surfaces to minimize computational costs.

The model is meshed using ANSYS Meshing software. An unstructured model mesh has been generated, consisting of 972354 cells.

Computational Fluid Dynamics (CFD) Method

In this simulation, the stator section remains static, with all its walls defined as stationary walls. On the other hand, the rotor section is designated as a mobile area using the Frame Motion method in cell zone conditions, and all the walls associated with this section are also capable of movement.

Thus, a rotational motion is established for the airflow in the rotor area, with a rotational velocity of 25,000 rpm. In addition, given the model's focus on pressure changes, the pressure boundary condition is applied both at the input and the output.

A multistage compressor featuring two rotors and two stators. In summary

Following the simulation, we have obtained two-dimensional and three-dimensional contours that depict pressure, velocity, turbulence kinetic energy, and pressure gradient.

In addition, the airflow pathlines within the compressor are acquired in three dimensions. In addition, pressure and wall tension contours have been obtained for various parts of the blades, rotor, and stator.

The findings indicate that the airflow pressure rises as the horizontal airflow moves in line with the central axis of the compressor. In addition, the pathlines effectively illustrate the rotational motion around the rotors and stators.

The problem involves numerically simulating the ventilation flow in a tube for air suction using ANSYS Fluent software.

We utilized the Design Modeler software to create the 3-D model.

We use ICEM software to mesh the model.

The mesh type is structured, and the element number is 193932.

The simulation relies on time and is conducted transiently.

We utilize the VOF multiphase model to accurately characterize a two-phase flow.

Overview

In the given problem, a CFD simulation of airflow inside a venturi and accurate modeling of air bubbles as a separate phase in water is performed using ANSYS Fluent software. When the fluid flows through the narrow part of the pipe, the pressure in the fluid is reduced due to the venturi effect.

The velocity increases when the pipe diameter decreases based on the continuity equation, and the pressure decreases because of energy conservation. Kinetic energy balance is achieved through the drop in pressure or the pressure gradient. The current model is created in three dimensions using SOLIDWORKS and then imported into the Design Modeler.

The current project's meshing has been completed using ICEM software. The elements are initially employed in a hexahedral configuration, resulting in reduced cells and improved quality. The element number is 193932, and the mesh type is structured. In addition, the transient solver has been enabled to address the current issue.

Approach

For this particular problem, we will conduct a CFD simulation of airflow inside a Venturi using the VOF multiphase model. We also ensure accurate modeling of air bubbles as a separate phase in water. As expected, the mixed air stream enters the venturi with a volume fraction of 0.7.

Once the stream passes through the bottleneck, its flow rate increases while the pressure decreases. The pressure drop results in air being extracted from the hole in the ventricle. As more air is introduced into the stream, the volume fraction of air increases.

All the inputs and outputs of this problem were operating under a pressure of 30 bar. This study examines the quantity of air drawn into the venturi and its subsequent injection into water.

The VOF model is highly effective, straightforward, and well-suited for accurately determining the interface boundary between phases in multiphase flow. This model is based on the older MAC: cell and marker model, specifically for tracking volumes. It utilizes a tracking-surface model to achieve accurate results.

In the VOF model, the momentum equations are solved together for all phases, while each phase has its own volume fraction equation of the continuity equation. One can achieve a highly precise simulation of the phase boundary by utilizing the Set Level model in the (VOF + Set Level Couple) section.

VOF has been meticulously crafted to monitor and establish the demarcation line between different phases accurately. This model is designed to simulate immiscible multiphase flow with collisions and clear boundaries between phases.

The Venturi tube features two distinct inlets. The air and water mixture, with a water content of 70% (volume fraction 0.7), enters through the main inlet boundary. As a result of the pressure changes at the bottleneck, air can enter through the top boundary because of the pressure inlet boundary condition type.

In summary

After completing the solution process, you will obtain two-dimensional contours that depict the velocity, pressure, air and water volume fraction, streamlines, and more within the domain.

As observed in the water volume fraction contour, the incoming water flow's velocity induces air intake into the venturi, resulting in the formation of a two-phase (air-water) fluid. There are visible air bubbles present in the water fluid.

In addition, the data obtained from the Fluent software reveals a graph illustrating the magnitude of air intake through the air inlet over time.

When water flows through a narrow section of a venturi tube, it creates a vacuum at the end of the section. At the location where the vacuum occurs, a hole in the pipe causes air to be drawn into the mainstream, resulting in a turbulent flow.